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class="menus_item"><a class="site-page" href="/about/"><i class="fa-fw fas fa-heart"></i><span> 关于</span></a></div></div><div id="toggle-menu"><a class="site-page"><i class="fas fa-bars fa-fw"></i></a></div></div></nav><div id="post-info"><h1 class="post-title">气溶胶分类方法——AOD与AE阈值法分类</h1><div id="post-meta"><div class="meta-firstline"><span class="post-meta-date"><i class="far fa-calendar-alt fa-fw post-meta-icon"></i><span class="post-meta-label">发表于</span><time class="post-meta-date-created" datetime="2023-09-21T00:48:07.000Z" title="发表于 2023-09-21 08:48:07">2023-09-21</time><span class="post-meta-separator">|</span><i class="fas fa-history fa-fw post-meta-icon"></i><span class="post-meta-label">更新于</span><time class="post-meta-date-updated" datetime="2023-09-21T13:56:52.555Z" title="更新于 2023-09-21 21:56:52">2023-09-21</time></span><span class="post-meta-categories"><span class="post-meta-separator">|</span><i class="fas fa-inbox fa-fw post-meta-icon"></i><a class="post-meta-categories" href="/categories/%E7%A0%94%E7%A9%B6%E6%96%B9%E6%B3%95/">研究方法</a></span></div><div class="meta-secondline"><span class="post-meta-separator">|</span><span class="post-meta-wordcount"><i class="far fa-file-word fa-fw post-meta-icon"></i><span class="post-meta-label">字数总计:</span><span class="word-count">981</span><span class="post-meta-separator">|</span><i class="far fa-clock fa-fw post-meta-icon"></i><span class="post-meta-label">阅读时长:</span><span>5分钟</span></span><span class="post-meta-separator">|</span><span class="post-meta-pv-cv" id="" data-flag-title="气溶胶分类方法——AOD与AE阈值法分类"><i class="far fa-eye fa-fw post-meta-icon"></i><span class="post-meta-label">阅读量:</span><span id="busuanzi_value_page_pv"></span></span></div></div></div></header><main class="layout" id="content-inner"><div id="post"><article class="post-content" id="article-container"><h1 id="AOD与AE阈值法原理"><a href="#AOD与AE阈值法原理" class="headerlink" title="AOD与AE阈值法原理"></a>AOD与AE阈值法原理</h1><p>气溶胶光学厚度AOD（Aerosol Optical Depth）用以表征气溶胶在大气纵向空气柱密度大小的量，是一个没有量纲的量；波长指数AE（Angstrom Exp）用以表征气溶胶的粒径大小的物理量，通常情况下，气溶胶粒子越大，AE越小。</p>
<h2 id="向量空间"><a href="#向量空间" class="headerlink" title="向量空间"></a>向量空间</h2><p>本研究代码利用AOD与AE建立向量空间，对气溶胶进行逐像元聚类。</p>
<h1 id="MCD19A2数据介绍"><a href="#MCD19A2数据介绍" class="headerlink" title="MCD19A2数据介绍"></a>MCD19A2数据介绍</h1><p>所用数据为MODIS 1KM的气溶胶产品MCD19A2，数据来源于<a target="_blank" rel="noopener external nofollow noreferrer" href="https://code.earthengine.google.com/b5dce31d93d00be9b561eb20e626d7b0?noload=1">Google Earth Engine</a><br>(需科学上网)<br>下载数据代码如下：</p>
<figure class="highlight javascript"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">//这是导入的影像和你的矢量边界</span></span><br><span class="line"><span class="keyword">var</span> table = ee.<span class="title class_">FeatureCollection</span>(<span class="string">&quot;projects/ee-guojiaxiang0820/assets/ChineseSea&quot;</span>);</span><br><span class="line"><span class="comment">//对你的要下载的影像进行时间和边界的筛选</span></span><br><span class="line"><span class="keyword">var</span> collection = ee.<span class="title class_">ImageCollection</span>(<span class="string">&#x27;MODIS/006/MCD19A2_GRANULES&#x27;</span>)</span><br><span class="line">                  .<span class="title function_">select</span>(<span class="string">&#x27;Optical_Depth_055&#x27;</span>)</span><br><span class="line">                  .<span class="title function_">filterDate</span>(<span class="string">&#x27;2022-03-28&#x27;</span>, <span class="string">&#x27;2022-03-29&#x27;</span>)</span><br><span class="line">                  .<span class="title function_">filterBounds</span>(table);</span><br><span class="line"><span class="comment">//波段的配色方案一般按照官方提供的默认状态就行</span></span><br><span class="line"><span class="keyword">var</span> band_viz = &#123;</span><br><span class="line">  <span class="attr">min</span>: <span class="number">0</span>,</span><br><span class="line">  <span class="attr">max</span>: <span class="number">500</span>,</span><br><span class="line">  <span class="attr">palette</span>: [<span class="string">&#x27;black&#x27;</span>, <span class="string">&#x27;blue&#x27;</span>, <span class="string">&#x27;purple&#x27;</span>, <span class="string">&#x27;cyan&#x27;</span>, <span class="string">&#x27;green&#x27;</span>, <span class="string">&#x27;yellow&#x27;</span>, <span class="string">&#x27;red&#x27;</span>]</span><br><span class="line">&#125;;</span><br><span class="line"><span class="comment">//加载影像和设置中心位置以及缩放</span></span><br><span class="line"><span class="title class_">Map</span>.<span class="title function_">addLayer</span>(collection.<span class="title function_">mean</span>(), band_viz, <span class="string">&#x27;Optical Depth 055&#x27;</span>);</span><br><span class="line"><span class="title class_">Map</span>.<span class="title function_">setCenter</span>(<span class="number">115</span>, <span class="number">38</span>, <span class="number">4</span>);</span><br><span class="line"></span><br><span class="line"><span class="comment">//想融合多起数据，可以用mosaic或者最大合成qualityMosaic</span></span><br><span class="line"><span class="comment">//如果这里不选择波段进行镶嵌的话，等的时间会很长很长</span></span><br><span class="line"><span class="keyword">var</span> image=collection.<span class="title function_">qualityMosaic</span>(<span class="string">&#x27;Optical_Depth_055&#x27;</span>).<span class="title function_">clip</span>(table);</span><br><span class="line"><span class="comment">//导出影像</span></span><br><span class="line"><span class="title class_">Export</span>.<span class="property">image</span>.<span class="title function_">toDrive</span>(&#123;</span><br><span class="line">  <span class="attr">image</span>:image.<span class="title function_">select</span>(<span class="string">&#x27;Optical_Depth_055&#x27;</span>),</span><br><span class="line">  <span class="attr">description</span>: <span class="string">&#x27;aod_055_1km_20220328_avr&#x27;</span>,</span><br><span class="line">  <span class="attr">folder</span>: <span class="string">&#x27;ChineseSea&#x27;</span>,</span><br><span class="line">  <span class="attr">scale</span>: <span class="number">1000</span>,</span><br><span class="line">  <span class="attr">region</span>:table</span><br><span class="line">&#125;);</span><br><span class="line"></span><br><span class="line"><span class="title class_">Map</span>.<span class="title function_">addLayer</span>(image, band_viz,<span class="string">&#x27;aod&#x27;</span>);</span><br><span class="line"><span class="title class_">Map</span>.<span class="title function_">addLayer</span>(table, &#123;&#125;,<span class="string">&#x27;china&#x27;</span>); </span><br></pre></td></tr></table></figure>
<blockquote>
<p><a target="_blank" rel="noopener external nofollow noreferrer" href="https://pan.baidu.com/s/1-DXuNMzeSBl3mXBss2FkWA">MCD19A2 AOD数据示例</a></p>
<p>提取码：jjgg</p>
<p><a target="_blank" rel="noopener external nofollow noreferrer" href="https://pan.baidu.com/s/1w4Mwxv-usjbv4ZwUPoz1Yg">矢量数据</a></p>
<p>提取码：jjgg</p>
</blockquote>
<h1 id="Python代码实现"><a href="#Python代码实现" class="headerlink" title="Python代码实现"></a>Python代码实现</h1><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span 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class="line">89</span><br><span class="line">90</span><br><span class="line">91</span><br><span class="line">92</span><br><span class="line">93</span><br><span class="line">94</span><br><span class="line">95</span><br><span class="line">96</span><br><span class="line">97</span><br><span class="line">98</span><br><span class="line">99</span><br><span class="line">100</span><br><span class="line">101</span><br><span class="line">102</span><br><span class="line">103</span><br><span class="line">104</span><br><span class="line">105</span><br><span class="line">106</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># -*- coding: utf-8 -*-</span></span><br><span class="line"><span class="string">&#x27;&#x27;&#x27;</span></span><br><span class="line"><span class="string">@Time ： 2023/9/7 16:08</span></span><br><span class="line"><span class="string">@Auth ： Guo Jiaxiang</span></span><br><span class="line"><span class="string">@Blog : https://www.guojxblog.cn</span></span><br><span class="line"><span class="string">@GitHub : https://github.com/guojx0820</span></span><br><span class="line"><span class="string">@Email : guojx0820@gmail.com</span></span><br><span class="line"><span class="string">&#x27;&#x27;&#x27;</span></span><br><span class="line"><span class="keyword">import</span> os</span><br><span class="line"><span class="keyword">import</span> time</span><br><span class="line"><span class="keyword">import</span> numpy <span class="keyword">as</span> np</span><br><span class="line"><span class="keyword">from</span> osgeo <span class="keyword">import</span> gdal, osr</span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="keyword">class</span> <span class="title class_">Retrieval_AOD_AE_Classification</span>:</span><br><span class="line">    <span class="keyword">def</span> <span class="title function_">__init__</span>(<span class="params">self</span>):</span><br><span class="line">        self.geo_resolution = <span class="number">0.01</span></span><br><span class="line"></span><br><span class="line">    <span class="keyword">def</span> <span class="title function_">_read_tiff_mcd_</span>(<span class="params">self, aod_550_file, aod_470_file</span>):</span><br><span class="line">        aod_550_dataset = gdal.Open(aod_550_file)</span><br><span class="line">        aod_470_dataset = gdal.Open(aod_470_file)</span><br><span class="line">        aod_550_data = aod_550_dataset.ReadAsArray() * <span class="number">0.001</span></span><br><span class="line">        aod_470_data = aod_470_dataset.ReadAsArray() * <span class="number">0.001</span></span><br><span class="line">        geo_transform = aod_550_dataset.GetGeoTransform()</span><br><span class="line">        projection = aod_550_dataset.GetProjection()</span><br><span class="line">        <span class="keyword">return</span> aod_550_data, aod_470_data, geo_transform, projection</span><br><span class="line"></span><br><span class="line">    <span class="keyword">def</span> <span class="title function_">_ae_470_550_cal_</span>(<span class="params">self, aod_550_data, aod_470_data, geo_transform, projection</span>):</span><br><span class="line">        lon_min = geo_transform[<span class="number">0</span>]</span><br><span class="line">        lat_max = geo_transform[<span class="number">3</span>]</span><br><span class="line">        geo_resolution_row = geo_transform[<span class="number">1</span>]</span><br><span class="line">        geo_resolution_col = geo_transform[<span class="number">5</span>]</span><br><span class="line">        ae_470_550_data = -(np.log(aod_470_data / aod_550_data)) / (np.log(<span class="number">470</span> / <span class="number">550</span>))</span><br><span class="line">        <span class="keyword">return</span> ae_470_550_data, lon_min, lat_max, geo_resolution_row, geo_resolution_col</span><br><span class="line"></span><br><span class="line">    <span class="keyword">def</span> <span class="title function_">_traditional_method_classification_</span>(<span class="params">self, aod550, ae470_550</span>):</span><br><span class="line">        tra_type = np.empty((aod550.shape[<span class="number">0</span>], aod550.shape[<span class="number">1</span>]), dtype=np.float32)</span><br><span class="line">        <span class="keyword">for</span> i_raw <span class="keyword">in</span> <span class="built_in">range</span>(tra_type.shape[<span class="number">0</span>]):</span><br><span class="line">            <span class="keyword">for</span> j_col <span class="keyword">in</span> <span class="built_in">range</span>(tra_type.shape[<span class="number">1</span>]):</span><br><span class="line">                aod_temp = np.<span class="built_in">round</span>(aod550[i_raw, j_col], <span class="number">3</span>)</span><br><span class="line">                ae_temp = np.<span class="built_in">round</span>(ae470_550[i_raw, j_col], <span class="number">3</span>)</span><br><span class="line">                <span class="keyword">if</span> aod_temp == <span class="number">0.</span> <span class="keyword">and</span> ae_temp == <span class="number">0.</span>:</span><br><span class="line">                    tra_type[i_raw, j_col] = <span class="number">0.</span>  <span class="comment"># No Data</span></span><br><span class="line">                <span class="keyword">elif</span> aod_temp &gt; <span class="number">0.5</span> <span class="keyword">and</span> ae_temp &gt; <span class="number">1.0</span>:</span><br><span class="line">                    tra_type[i_raw, j_col] = <span class="number">1.</span>  <span class="comment"># BB</span></span><br><span class="line">                <span class="keyword">elif</span> aod_temp &lt; <span class="number">0.5</span> <span class="keyword">and</span> ae_temp &gt; <span class="number">1.0</span>:</span><br><span class="line">                    tra_type[i_raw, j_col] = <span class="number">2.</span>  <span class="comment"># CC</span></span><br><span class="line">                <span class="keyword">elif</span> aod_temp &lt; <span class="number">0.5</span> <span class="keyword">and</span> ae_temp &lt; <span class="number">1.0</span>:</span><br><span class="line">                    tra_type[i_raw, j_col] = <span class="number">3.</span>  <span class="comment"># CM</span></span><br><span class="line">                <span class="keyword">elif</span> aod_temp &gt; <span class="number">0.5</span> <span class="keyword">and</span> ae_temp &lt; <span class="number">0.7</span>:</span><br><span class="line">                    tra_type[i_raw, j_col] = <span class="number">4.</span>  <span class="comment"># DD</span></span><br><span class="line">                <span class="keyword">else</span>:</span><br><span class="line">                    tra_type[i_raw, j_col] = <span class="number">5.</span>  <span class="comment"># MX</span></span><br><span class="line">        <span class="keyword">return</span> tra_type</span><br><span class="line"></span><br><span class="line">    <span class="keyword">def</span> <span class="title function_">_write_tiff_</span>(<span class="params">self, data, lon_min, lat_max, geo_resolution_row, geo_resolution_col, out_name</span>):</span><br><span class="line">        <span class="keyword">if</span> data.ndim == <span class="number">3</span>:</span><br><span class="line">            band_count, rows, cols = data.shape</span><br><span class="line">        <span class="keyword">else</span>:</span><br><span class="line">            band_count, (rows, cols) = <span class="number">1</span>, data.shape</span><br><span class="line">        driver = gdal.GetDriverByName(<span class="string">&#x27;GTiff&#x27;</span>)</span><br><span class="line">        out_raster = driver.Create(out_name, cols, rows, band_count, gdal.GDT_Float32)</span><br><span class="line">        out_raster.SetGeoTransform((lon_min, geo_resolution_row, <span class="number">0</span>, lat_max, <span class="number">0</span>, geo_resolution_col))</span><br><span class="line">        out_raster_SRS = osr.SpatialReference()</span><br><span class="line">        <span class="comment"># 代码4326表示WGS84坐标</span></span><br><span class="line">        out_raster_SRS.ImportFromEPSG(<span class="number">4326</span>)</span><br><span class="line">        out_raster.SetProjection(out_raster_SRS.ExportToWkt())</span><br><span class="line">        <span class="keyword">if</span> band_count == <span class="number">1</span>:</span><br><span class="line">            out_raster.GetRasterBand(<span class="number">1</span>).WriteArray(data)</span><br><span class="line">        <span class="keyword">else</span>:</span><br><span class="line">            <span class="comment"># 获取数据集第一个波段，是从1开始，不是从0开始</span></span><br><span class="line">            <span class="keyword">for</span> i_band_count <span class="keyword">in</span> <span class="built_in">range</span>(band_count):</span><br><span class="line">                out_raster.GetRasterBand(i_band_count + <span class="number">1</span>).WriteArray(data[i_band_count])</span><br><span class="line">        out_raster.FlushCache()</span><br><span class="line">        <span class="keyword">del</span> out_raster</span><br><span class="line">        out_raster = <span class="literal">None</span></span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="keyword">if</span> __name__ == <span class="string">&#x27;__main__&#x27;</span>:</span><br><span class="line">    start_time = time.time()</span><br><span class="line">    input_directory = <span class="string">&#x27;/mnt/d/Experiments/Aerosol_Classification/Data/MCD19A2/&#x27;</span></span><br><span class="line">    output_directory = <span class="string">&#x27;/mnt/d/Experiments/Aerosol_Classification/Data/Results/MCD_Cls/&#x27;</span></span><br><span class="line">    <span class="keyword">if</span> os.path.exists(output_directory) == <span class="literal">False</span>:</span><br><span class="line">        os.makedirs(output_directory)</span><br><span class="line">    <span class="keyword">for</span> root, dirs, files <span class="keyword">in</span> os.walk(input_directory):</span><br><span class="line">        aod550_file_list = [input_directory + i_tif <span class="keyword">for</span> i_tif <span class="keyword">in</span> files <span class="keyword">if</span></span><br><span class="line">                            i_tif.endswith(<span class="string">&#x27;20220328_avr.tif&#x27;</span>) <span class="keyword">and</span> i_tif.startswith(<span class="string">&#x27;aod_055&#x27;</span>, <span class="number">0</span>)]</span><br><span class="line">        aod470_file_list = [input_directory + i_tif <span class="keyword">for</span> i_tif <span class="keyword">in</span> files <span class="keyword">if</span></span><br><span class="line">                            i_tif.endswith(<span class="string">&#x27;20220328_avr.tif&#x27;</span>) <span class="keyword">and</span> i_tif.startswith(<span class="string">&#x27;aod_047&#x27;</span>, <span class="number">0</span>)]</span><br><span class="line">    retr_aod_ae = Retrieval_AOD_AE_Classification()</span><br><span class="line">    <span class="keyword">for</span> i_aod550, j_aod470 <span class="keyword">in</span> <span class="built_in">zip</span>(aod550_file_list, aod470_file_list):</span><br><span class="line">        single_start_time = time.time()</span><br><span class="line">        out_name = output_directory + <span class="built_in">str</span>(os.path.basename(i_aod550)[<span class="number">12</span>:<span class="number">20</span>]) + <span class="string">&#x27;_MCD_Cls.tiff&#x27;</span></span><br><span class="line">        aod_550_data, aod_470_data, geo_transform, projection = retr_aod_ae._read_tiff_mcd_(i_aod550, j_aod470)</span><br><span class="line">        ae_470_550_data, lon_min, lat_max, geo_resolution_row, geo_resolution_col = retr_aod_ae._ae_470_550_cal_(</span><br><span class="line">            aod_550_data, aod_470_data, geo_transform, projection)</span><br><span class="line">        tra_type = retr_aod_ae._traditional_method_classification_(aod_550_data, ae_470_550_data)</span><br><span class="line">        retr_aod_ae._write_tiff_(tra_type, lon_min, lat_max, geo_resolution_row, geo_resolution_col, out_name)</span><br><span class="line">        single_end_time = time.time()</span><br><span class="line">        single_run_time = np.<span class="built_in">round</span>(single_end_time - single_start_time, <span class="number">3</span>)</span><br><span class="line">        <span class="built_in">print</span>(<span class="string">&#x27;The data &#x27;</span> + <span class="built_in">str</span>(os.path.basename(i_aod550)[<span class="number">12</span>:<span class="number">20</span>]) + <span class="string">&#x27; are classified, the time cosuming is &#x27;</span> +</span><br><span class="line">              <span class="built_in">str</span>(single_run_time) + <span class="string">&#x27; s.&#x27;</span>)</span><br><span class="line">    end_time = time.time()</span><br><span class="line">    total_run_time = np.<span class="built_in">round</span>(end_time - start_time, <span class="number">3</span>)</span><br><span class="line">    <span class="built_in">print</span>(<span class="string">&#x27;All the data are classified, the time cosuming is &#x27;</span> + <span class="built_in">str</span>(total_run_time) + <span class="string">&#x27; s.&#x27;</span>)</span><br><span class="line"> </span><br></pre></td></tr></table></figure>
<h1 id="结果"><a href="#结果" class="headerlink" title="结果"></a>结果</h1><p><img src="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/loading3.gif" data-original="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/AOD_AE_Classification/aod_047_20210310.png" alt="AOD_470nm 2021/03/10"><br><img src="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/loading3.gif" data-original="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/AOD_AE_Classification/aod_055_20210310.png" alt="AOD_550nm 2021/03/10"><br><img src="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/loading3.gif" data-original="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/AOD_AE_Classification/Cls.png" alt="2021/03/10 分类结果示例"></p>
</article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta">文章作者: </span><span class="post-copyright-info"><a href="mailto:guojiaxiang0820@gmail.com" rel="external nofollow noreferrer">洛沐</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta">文章链接: </span><span class="post-copyright-info"><a href="https://www.guojxblog.cn/archives/f863e629.html">https://www.guojxblog.cn/archives/f863e629.html</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta">版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/" rel="external nofollow noreferrer" target="_blank">CC BY-NC-SA 4.0</a> 许可协议。转载请注明来自 <a href="https://www.guojxblog.cn" target="_blank">洛沐の人间客栈</a>！</span></div></div><div class="tag_share"><div class="post-meta__tag-list"><a class="post-meta__tags" href="/tags/%E5%A4%A7%E6%B0%94%E4%B8%8E%E7%AE%97%E6%B3%95/">大气与算法</a></div><div class="post_share"><div class="social-share" data-image="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/AOD_AE_Classification/amiya.jpg" data-sites="facebook,twitter,wechat,weibo,qq"></div><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/social-share.js/dist/css/share.min.css" media="print" onload="this.media='all'"><script src="https://cdn.jsdelivr.net/npm/social-share.js/dist/js/social-share.min.js" defer></script></div></div><div class="post-reward"><div class="reward-button"><i class="fas fa-qrcode"></i> 打赏</div><div class="reward-main"><ul class="reward-all"><li class="reward-item"><a href="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/wechat.jpeg" rel="external nofollow noreferrer" target="_blank"><img class="post-qr-code-img" src="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/loading3.gif" data-original="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/wechat.jpeg" alt="微信"/></a><div class="post-qr-code-desc">微信</div></li><li class="reward-item"><a href="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/alipay.jpeg" rel="external nofollow noreferrer" target="_blank"><img class="post-qr-code-img" src="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/loading3.gif" data-original="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/alipay.jpeg" alt="支付宝"/></a><div class="post-qr-code-desc">支付宝</div></li></ul></div></div><nav class="pagination-post" id="pagination"><div class="next-post pull-full"><a href="/archives/6f5df5c1.html"><img class="next-cover" src="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/loading3.gif" data-original="https://luomublog.oss-cn-qingdao.aliyuncs.com/ImgHost/CNN/DNN_top.jpeg" onerror="onerror=null;src='/img/404.jpg'" alt="cover of next post"><div class="pagination-info"><div class="label">下一篇</div><div class="next_info">Tensorflow深度学习——神经网络</div></div></a></div></nav><hr/><div id="post-comment"><div class="comment-head"><div class="comment-headline"><i class="fas fa-comments fa-fw"></i><span> 评论</span></div></div><div class="comment-wrap"><div><div id="lv-container" data-id="city" data-uid="MTAyMC81NjIzOS8zMjcwMg=="></div></div></div></div></div><div class="aside-content" id="aside-content"><div class="sticky_layout"><div class="card-widget" id="card-toc"><div class="item-headline"><i class="fas fa-stream"></i><span>目录</span><span class="toc-percentage"></span></div><div class="toc-content is-expand"><ol class="toc"><li class="toc-item toc-level-1"><a class="toc-link" href="#AOD%E4%B8%8EAE%E9%98%88%E5%80%BC%E6%B3%95%E5%8E%9F%E7%90%86"><span class="toc-number">1.</span> <span class="toc-text">AOD与AE阈值法原理</span></a><ol class="toc-child"><li class="toc-item toc-level-2"><a class="toc-link" href="#%E5%90%91%E9%87%8F%E7%A9%BA%E9%97%B4"><span class="toc-number">1.1.</span> <span class="toc-text">向量空间</span></a></li></ol></li><li class="toc-item toc-level-1"><a class="toc-link" href="#MCD19A2%E6%95%B0%E6%8D%AE%E4%BB%8B%E7%BB%8D"><span class="toc-number">2.</span> <span class="toc-text">MCD19A2数据介绍</span></a></li><li class="toc-item toc-level-1"><a class="toc-link" href="#Python%E4%BB%A3%E7%A0%81%E5%AE%9E%E7%8E%B0"><span class="toc-number">3.</span> <span class="toc-text">Python代码实现</span></a></li><li class="toc-item toc-level-1"><a class="toc-link" href="#%E7%BB%93%E6%9E%9C"><span class="toc-number">4.</span> <span class="toc-text">结果</span></a></li></ol></div></div></div></div></main><footer id="footer"><div id="footer-wrap"><div class="copyright">&copy;2021 - 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